Coforge's Data Cosmos AutoClassifier

AutoClassifier is Coforge's AI/ML-powered data classification and tagging accelerator engineered to automate end-to-end data confidentiality classification across enterprise data estates on Azure. Originally designed and implemented for a large CPG client to address manual and inconsistent data confidentiality tagging across large, distributed datasets, it is now part of Coforge Data Cosmos™ — the innovation backbone combining platforms, agentic accelerators, and services for end-to-end data engineering, BI, governance, and analytics.

The platform combines intelligent rule-based classification, AI/ML model-driven tagging, human-in-the-loop validation, and continuous learning to deliver high-precision, scalable classification: • Rule-Based Classification – regex patterns, keyword matching, and data type analysis • AI/ML-Driven Tagging – models trained on domain-specific patterns for confidentiality levels and sensitivity categories • Human-in-the-Loop (HITL) – steward checkpoints for verification and quality scoring • Continuous Learning – feedback-driven retraining to improve model precision • Catalog Integration – export classified metadata to catalogs and business glossaries

Key Benefits: reduces manual classification effort by 60%+, achieves 75–90% re-run stability, accelerates data onboarding, and provides audit-ready traceability for GDPR, HIPAA, PCI DSS, and BCBS 239.

Key Use Cases: • CPG & Retail – confidentiality classification across product, supply chain, and customer data • Banking – sensitivity classification across customer, transaction, and risk data for BCBS 239, PCI DSS • Insurance – policyholder PII classification across policy admin, claims, and billing • Healthcare – PHI detection across EMR/EHR systems for HIPAA enforcement • Travel & Hospitality – guest and passenger data classification for GDPR and PCI DSS

The 8-week implementation engagement covers: discovery and metadata profiling, platform deployment on Azure, rule-based and AI/ML classification configuration, HITL workflow setup, continuous learning enablement, catalog/glossary integration, and knowledge transfer.

Target Audience: Data Governance & Stewardship Teams, Data Engineering & Platform Teams, Compliance & Risk Officers, Data Architects, and Analytics Leaders.